Visualized Failure Prediction for the Masonry Great Wall

A novel hybrid approach combining architectural visualization with structural collapse simulation successfully predicts failure mechanisms in the Ming Great Wall (1368–1644 AD). Using Blender and a physics engine, researchers modeled four damage types—stone layer collapse, step collapse, parapet wall inward tilting, and stone layer bulge—based on brick dimensions, friction coefficients, and adhesive strength. The method accurately visualizes failure processes and assesses structural stability, offering preliminary engineering insights. This study demonstrates the potential of digital tools to analyze and preserve the Great Wall’s integrity under natural and artificial threats.

Du, H., Yu, J., Wang, Y., Zhu, Y., Tang, Y., & Wang, H. (2022). Visualized Failure Prediction for the Masonry Great Wall. Buildings, 12(12), 2224. https://doi.org/10.3390/buildings12122224